I’ve been trying to put into practice all the concepts (or as much of the concepts as I can) I learnt in level 2, hoping that those concepts will sink in completely and that I can retain them for a little longer.
I’m trying to put everything in practice by evaluating a company (listed on Karachi Stock Exchange (KSE) … FFC). For those who are not very familiar, Karachi is a city in Pakistan, a country in south asia; a 3rd world country. Since we are a developing country, our financial markets are week and we are way behind many developed countries and therefore a lot of data, that might otherwise be available in developed markets, is not available to us here.
Anyway, enough of background building and coming to the point. Currently, I am trying to put into practice the “FAMA FRENCH” model for calculating “required rate of return” but I do not know where to look for the data, or more importantly, how to calculate the bits of data needed to complete the analysis, myself. I am struggling to calculate betas for all three factors (size, value/growth and liquidity) and also the coffecients for each of the three factors.
To calculate the size of the subject company, I’ve taken its assets and I am comparing its assets with an average company listed on KSE. For calculating coffecients for value/growth I have calculated p/bv of the subject and compared it with the average industry p/bv and finally for calculating volume’s coffecient, I’m taking the average monthly trading volume of the subject and comparing it to the average trading volume of the industry.
Please advise me if this is the correct approach? Also help me in calculating betas for all three factors. We do not have any publicly available data to fall to. Any help will be highly appreciated
To use the fama and french models, you require historical time series of the factor returns.
To do this, you need data for the whole exchange you are interested in, then you need to define breakpoints on what you call large, mid and small companies as well as value/growth companies. For instance, your breakpoints for “large” could be 90th percentile, so you take the top 10% largest companies on the exchange and call them “Large”…you do the same for mid and small. Once you have your portfolios defined, then you use historical returns of these portfolios to estimate the coefficients, by regressing against the entire market.
As you can see that this is a tedious, time consuming approach that requires a lot of data that is not probably available, I wouldn’t recommend it at all.
Many people rather than build the portfolios up from bottom to top like Fama and French, simply make use of the historical returns on market proxies such as “MSCI Large Cap index”, “MSCI value index” etc …but these are only suitable for developed economies.
I think your best bet here is to use an extended CAPM
One more thing, the company I am trying to evaluate is from fertilizers sector. In order to forecast its next quarter’s sales, I am going to regress the historical sales data against some factors. The factors I am using here are GDP, government subsidies and natural calamities like floods (floods have historically increased next year’s sales).
We have analysts forecasts available on sales and I could use them and it will make my life a lot easier. But the point of this exercise is to put into practice the concepts I learnt so that they can be retained.
The question that I forgot to ask in my last post is, that I am not sure how these three factors will explain the sales of the company, and adding more factors here will make life very difficult.
Can you suggest me any other way of forecasting sales. I’ve calculated year on year change in sales for last 5 years and I can take an average of it and use it for my analysis but that wont make me look too nerdy
our instructor showed us the real life application of Private Company Valuation techniques, and that was a case of valuing a Pakistani poultry business… i was surprized to see that exactly the same valuation techniques were applied as we learnt. e.g GPCM GTM
I think a really rich way of forecasting sales is associating future sales to its fundamentals. For this, you will need to do some information gathering - this will be tasking, but at the end, you will see that you have learnt a lot about the company than you ever thought you could.
I will start with the annual reports and study the director’s notes. here, you will normally see the company’s own forecasts of sales, notes on competion, industry, macro risks etc. this will normall give you a very solid starting point. (you might even get all you need for a sales forecast from here)
Then you will want to know who the company’s customers are? Are the goods being exported or sold exclusively locally? If it is being exported, what % of the country’s total export does the fertilizer industry make up for? If being sold exclusively locally then to whom? Is local sales affected by local consumption? Is local sales affected by local population growth? median household income? Are local farmers more likely to make use of fertilizers if they get some support from the Parkisani government? If yes, then historically, what % of government expenditure goes into Agriculture?
Then you may want to collect data on these variables - i.e %change in exports, %change in population growth, % change in median household income, % change in government expenditure…All of these may be employed in a time series model
The advantage of this is that you may be able to do some scenario type analysis and forecast the company’s sales if some variables change by a certain amount, e.g if exports increase by 1%.
Obviously, the disadvantage is the fact that it is time consuming, and may require data which may not be available. In which case, one other alternative i think may be worth pursing will be to look at the historical relationship between earning growth rate and sales - Usually, these two will be close, especially for a company that does not have huge depreciating assets. This relationship may then be used to forecast future sales once you have an estimate of growth rate.
Hi Panos, the below is an extract from Morningstar’s equity research methodology. It could help provide you with some thoughts on how some analysts go by their equity research. i think one thing you may find is that the theory is not much different from all you have come across in the CFA level 2, the application is however an individual thing. You must become somewhat obsessive and passionately curious with the stock you are looking at, no one or book can teach this, you only become better at it as you dig deeper. Additionally, methodologies can vary slightly depending on the industry you are looking at, when i first became obsessive with Rio Tinto and Ferexxpo, i found this paper very useful ----> (http://www.basinvest.ch/upload/pdf/Valuation_of_Metals_and_Mining_Companies.pdf) An Analyst at Morningstar shares her thoughts. When I ﬁrst picked up coverage of IDEC Pharmaceuticals in March 2002, I was prepared to analyze another overpriced, underdeveloped biotechnology company. It didn’t take long after navigating IDEC’s web site, reading through 10Ks and proxy statements, listening to archived quarterly conference calls, and talking to doctors and nurses before I sensed that IDEC wasn’t just a struggling biotech. I dug deeper to ﬁnd that it was among the few proﬁtable biotechnology ﬁrms to work its way along the drug development value chain. It had nearly all the components necessary to be a star within the industry. My ﬁrst task was to determine how IDEC had achieved its success (and whether the company could repeat it). I examined IDEC’s alliances with other ﬁrms and visited chief operating officer Bill Rohn to learn how the ﬁrm executed on that strategy. He answered questions such as why the company chose to build its manufacturing facilities before it had enough product to utilize the capacity, and how the company attracts and retains talent. I toured the facilities and spoke with key executives to learn about the ﬁrm’s approach to research and development. Gaining conﬁdence that IDEC’s strategy was well planned and executed, I assessed the company’s economic moat. Without the vast dollars in free cash ﬂow (as a percentage of sales IDEC was exceptionally strong) that more-mature ﬁrms Genentech and Amgen were bringing in, could IDEC sustain a consistent (and high) return on its invested capital? For answers, I looked to the demand for IDEC’s products. IDEC’s leading drug, Rituxan, didn’t face any direct competition. I spoke with several physicians and a nurse, who expressed enthusiasm for the drug’s beneﬁts (which study results conﬁrm). The consensus seemed to be that the drug’s beneﬁts far outweighed possible side effects such as nausea. Furthermore, several additional indications for the drug were showing positive signs in clinical trials. With IDEC’s concrete product demand, manufacturing capacity, and strong scientiﬁc capabilities, Morningstar’s Investment Policy Committee (IPC) signed off on the wide-moat rating I submitted for IDEC. Next I developed a discounted cash ﬂow model to calculate an intrinsic value for the ﬁrm. As with most drug-development companies Morningstar covers, I used a probability-based sales model for top-line sales growth. The biggest questions included: how many years would it be before IDEC begins earning big-pharmalike margins; what discount rate should I use, and should future cash ﬂows (when the company is presumably more stable and less risky than it is today) be discounted at the same rate or a lower rate; and how long will IDEC earn returns in excess of its cost of capital? To answer the last question, I turned to the economic moat. As a wide-moat ﬁrm, IDEC’s strong excess returns should fade to its cost of capital over a 20-year period (the standard time period used for Morningstar’s wide-moat stocks). For some inputs, I assumed similar biotech industry standards that we use for mature drug-development ﬁrms. After discussions with the IPC, I settled on my model inputs and fair value estimate-- one that indicated that although the company held promise, the stock was still overvalued
My .02 - If you want to do your own valuations for whatever reason, go right ahead. All this other garbage may be good practical application, but you don’t need practical application. You need CFAI textbook theory.
If you want to learn the Level 2 curriculum, then stop doing whatever you’re doing and pick up a CFAI or Schweser Level 2 book and do the practice questions in there.
Website design is lousy - but what do you expect from a finance prof? Anyways, interesting quote from his bio:
“I am lucky enough to be in a field where a little knowledge and a dose of common sense goes a long way, and achieving guru status seems relatively simple. What I do know is neither profound nor earth shattering, but I would like to share it on this site. In that pursuit, I have attempted to keep almost the entire site open and accessible, with the only shut-off portions representing powerpoint slides used by instructors (who use my books). Everything that I learn, do or write in the field of finance will be on this site sooner or later. I hope that you find the content useful and that you will share it with others. Good luck!”